Interpretive Summary: Stored-product insects cause damage to grain-based products in food processing plants and warehouses, but the development of effective integrated pest management programs has been hampered by a lack of reliable information on pest numbers and distribution. Pheromone trapping is an important monitoring tool, and contour mapping is often used to visualize the results of pheromone monitoring programs and to provide information about how pests are distributed. There are many techniques available to construct contour maps, but they all rely on the presence of spatial autocorrelation among traps (i.e., that traps close to each other will have insect captures that are more alike than between traps further apart). Using data on warehouse beetle pheromone trap capture from a warehouse, it was determined that often there was no spatial autocorrelation among traps. Our analysis indicated that traps should be closer than 30 m to increase probability of spatial autocorrelation. Six contour mapping techniques wer tested, but there was no significant difference among techniques in the accuracy (i.e., difference between observed and predicted values) of the contour maps generated, but one technique (IDW interpolation based on 5th polynomial order) was more robust. Loss or destrubtion of traps was shown to have a significant influence on the maps generated, and should be minimized to improve the ability to compare contour maps from different sampling dates. The results of this research can be used to improve the implementation and interpretation of pheromone monitoring programs.

Technical Abstract:
The purpose of this study was to examine the accuracy and robustness of inverse distance weighting (IDW), spline, and linear kriging interpolation techniques when used to generate contour maps of pheromone trap catches of the warehouse beetle, Trogoderma variabile Ballion. Pheromone trapping was conducted during nine weeks in a food warehouse, and two types of pheromone-baited traps, FLITe-TRAK traps and Pherocon II traps, were used. FLITe-TRAK traps caught significantly more T. variabile individuals than Pherocon II traps. The range of the spatial auto-correlation seemed to be shorter for FLITe-TRAK traps compared to Pherocon II traps, and the analysis suggested that monitoring with both trap types should be conducted with less than 30 m between trap sites in order to assure spatial auto-correlation. For most of the weekly trap catch data sets there was no clear relationship between lag distance and trap catch variance, and this suggested that contour mapping was only appropriate for a few of the weekl trap catches. It is therefore recommended that pheromone-baited trap catches from indoor environments with intensive human activity, such as food warehouses, should be subjected to a variogram analysis prior to interpolation and contour mapping. There was no significant difference in accuracy of contour maps produced with the six interpolation techniques, but the IDW interpolation based on a 5th polynomial order was significantly more robust than other examined interpolation techniques.